Abstract

In general, the machine learning process can be accelerated through the use of additional knowledge about the problem solution. For example, monomorphic typed Genetic Programming (GP) uses type information to reduce the search space and improve performance. Unfortunately, monomorphic typed GP also loses the generality of untyped GP: the generated programs are only suitable for inputs with the specified type. Polymorphic typed GP improves over monomorphic and untyped GP by allowing the type information to be

Citations